https://github.com/GPflow/GPflow
Revision 6baeb43b1d68518e6ba0074e702d014f0fe85865 authored by jch5f on 15 June 2018, 10:31:27 UTC, committed by James Hensman on 15 June 2018, 10:31:27 UTC
* Add scaling to studentT conditional variance

The conditional variance of the Student’s T distributions is
proportional to the square of the scale of the distribution.  See
https://en.wikipedia.org/wiki/Student%27s_t-distribution#In_terms_of_sca
ling_parameter_σ,_or_σ2.
I’ve incorporated the correct scaling factor.

* explicit scale dtype and tensor broadcasting

Added an explicit data type for the Student’s T scale parameter, and
made the broadcasting in the conditional_variance method explicit.
1 parent 916458e
Raw File
Tip revision: 6baeb43b1d68518e6ba0074e702d014f0fe85865 authored by jch5f on 15 June 2018, 10:31:27 UTC
Likelihood/students t variance scaling (#777)
Tip revision: 6baeb43
Dockerfile
# Copyright 2016 The GPflow authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

#USAGE:
#To run from prebuilt version use:
#docker run -it -p 8888:8888 gpflow/gpflow

#To replicate build use:
#docker build -t gpflow/gpflow .
#Assumes you are running from within cloned repo.

#Uses official Tensorflow docker for cpu only.
FROM tensorflow/tensorflow:1.0.0
COPY ./ /usr/local/GPflow/
RUN cd /usr/local/GPflow && \
    python setup.py develop && \
    rm /notebooks/*  && \
    apt-get clean  && \
    rm -rf /var/lib/apt/lists/*
COPY doc/source/notebooks/ LICENSE README.md /notebooks/
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